The present invention relates to a design support method adapted to obtain effective information for supporting design of a structure, for example, or to analyze behavior of an object in the field of fluid mechanics, thermodynamics, or electromagnetics.
According to a finite element method (abbreviated as FEM) as an approach to structural analysis, behaviors of even those structures which display complicated shapes or phenomena can be easily simulated with use of computers and related technology (software) that have been developed so far. In general, structures are subject to tolerance or dispersion in dimensions, material properties, etc. In order to work out a high-accuracy practical design, therefore, each structure must be examined in consideration of dispersion. Known evaluation methods for dispersion or reliability of structure that are applicable to structural analysis include a stochastic finite element method based on the Monte Carlo analysis, method of perturbation, or sensitivity analysis.
According to the structural analysis described above, structures having given shapes can be simply analyzed in strength and rigidity. If the result of the analysis indicates that the design target is not attained, therefore, the structural analysis must be repeated by the method of trial and error. In the case where a plurality of design variables are used, moreover, combinations of all the variables are numerous, so that calculations for these combinations require much time and high costs. According to the aforesaid stochastic finite element method, moreover, nonlinear problems require a lot of calculations. For these reasons, the acquisition of final optimal design data entails a waste of time and additional costs, so that change of design and the like cannot be tackled with speed.
In recent years, mechanical parts are designed by employing a simulation technique that is based on structural analysis. In order to improve the efficiency and accuracy of a design operation, it is advisable to obtain quantitative effectivity for design variables and utilize it for the settlement of the construction and set values of each mechanical part. The mechanical parts often display complicated nonlinear behaviors during use. These nonlinear behaviors (phenomena) of the mechanical parts change with load and time. According to conventional methods of optimization and effectivity analysis, therefore, the effectivity analysis and optimization calculation for the design variables of the mechanical parts inevitably require a very sophisticated algorithm and bulky computation.